Research interests ...

I'm involved in algorithmic projects in life sciences.
Paraphrasing our goals, progress in biomedical research is now highly
dependent on advanced computational techniques.
Computer Science plays a central role in devising techniques to search
and interpret the vast quantities of data that are generated by genome
sequencing and other biomedical technologies; to model complex
biological systems; and to make effective use of clinical and
diagnostic data.
Our research in this field draws on our expertise in knowledge
discovery, algorithms, and other fields.
(To be specific: string matching, compression, search, database algorithms, text
processing, parallelisation and distribution, machine learning, ...)
Like me, many researchers in this field don't have any formal background
in biology or bioinformatics, but nonetheless
the results of our research helps to provide important insights into
biological systems, as well as into the causes of diseases and their
possible treatments.

Another area of interest is how to get the greatest impact out of
our research, in particular, how to be sure that our results are correct
and how to accurately predict the behaviour of an algorithm in a
practical setting.
What basis should we have for choosing amongst methods?
What is the computing equivalent to the 'properties of materials' that
are necessary in engineering?

Some of my work is in text search and algorithms, in particular in the
biomedical context (see above) and problems in measurement (see above).

Always open to suggestions!
And ... new research students welcome. Speaking of which: